Human-centered design of an artificial intelligence monitoring system: the Vanderbilt Algorithmovigilance Monitoring and Operations System [0.03%]
以人为本的人工智能监控系统设计——范德比尔特算法监护及运营系统的开发
Megan E Salwei,Sharon E Davis,Carrie Reale et al.
Megan E Salwei et al.
Objectives: As the use of artificial intelligence (AI) in healthcare is rapidly expanding, there is also growing recognition of the need for ongoing monitoring of AI after implementation, called algorithmovigilance. Yet, ...
Kurmanbek Kaiyrbekov,Nicholas J Dobbins,Sean D Mooney
Kurmanbek Kaiyrbekov
Objectives: Phone surveys are crucial for collecting health data but are expensive, time-consuming, and difficult to scale. To overcome these limitations, we propose a survey collection approach powered by conversational ...
Meeting clinical recruitment milestones in an academic center: a data-driven, visual approach [0.03%]
基于数据和可视化的学术中心临床招募里程碑会议
Anna E Burns,John Tumberger,Mariah Brewe et al.
Anna E Burns et al.
Objectives: Describing the development of a visual dashboard leveraging available tools for efficient recruitment for patient centered clinical trials in resource constrained settings. ...
Evaluating the Impact of Electronic Health Record to Electronic Data Capture Technology on Workflow Efficiency: a Site Perspective [0.03%]
电子健康档案到电子数据捕获技术对工作流程效率的影响：一个中心的视角
Anna Patruno,Michael-Owen Panzarella,Michael Buckley et al.
Anna Patruno et al.
Introduction: Clinical trial data is still predominantly manually entered by site staff into Electronic Data Capture (EDC) systems. This process of abstracting and manually transcribing patient data is time-consuming, ine...
Engaging end-users to develop a novel algorithm to process electronic medication adherence monitoring device data [0.03%]
参与终端用户开发一种处理电子药物顺应性监控设备数据的新算法
Meghan E McGrady,Kevin A Hommel,Constance A Mara et al.
Meghan E McGrady et al.
Objective: To engage end-users to develop and evaluate an algorithm to convert electronic adherence monitoring device (EAMD) output into the adherence data required for analyses. ...
Assessing the acceptability and usability of MedSafer, a patient-centered electronic deprescribing tool [0.03%]
评估以患者为中心的电子停药工具MedSafer的接受度和易用性
Jimin J Lee,Eva Filosa,Tiphaine Pierson et al.
Jimin J Lee et al.
Background: Deprescribing is the clinically supervised process of stopping or reducing medications that are no longer beneficial. MedSafer is an electronic decision support tool that guides healthcare providers (HCPs) thr...
Mapping the overdose crisis: 6 locations using open medical examiner data [0.03%]
利用开放验尸官数据绘制药物滥用地图：六大地点
Daniel R Harris,Nicholas Anthony,Kelly A Keyes et al.
Daniel R Harris et al.
Objective: Medical examiners and coroners (ME/C) oversee medicolegal death investigations which determine causes of death and other contextual factors that may have influenced a death. We utilize open data releases from M...
Perceptions of and barriers to health information exchange use among emergency medicine and inpatient internal medicine clinicians in the Atlanta, Georgia metropolitan region [0.03%]
美国乔治亚州Atlanta地区急诊科和住院内科医务人员的健康信息交换使用情况及其影响因素和障碍因素的认识
Sara D Turbow,Priscilla H Kim,Camille P Vaughan et al.
Sara D Turbow et al.
Background: Health information exchanges (HIE), tools that electronically share clinical data across healthcare organizations, provide the opportunity to improve patient care. While widely available, HIE is utilized in on...
Deploying machine learning models in clinical settings: a real-world feasibility analysis for a model identifying adult-onset type 1 diabetes initially classified as type 2 [0.03%]
在临床环境中部署用于识别最初被误分类为2型糖尿病的成人突发性1型糖尿病模型的可行性分析
Irene Brusini,Suyin Lee,Jacob Hollingsworth et al.
Irene Brusini et al.
Objective: This study evaluates the performance and deployment feasibility of a machine learning (ML) model to identify adult-onset type 1 diabetes (T1D) initially coded as type 2 on electronic medical records (EMRs) from...
Implementing integrated genomic risk assessments for breast cancer: lessons learned from the Electronic Medical Records and Genomics study [0.03%]
从电子医疗记录与组学研究中学习到的关于乳腺癌综合基因组风险评估实施的经验教训
Cong Liu,Katherine D Crew,Jennifer Morse et al.
Cong Liu et al.
Objectives: To implementation an automated multi-institutional pipeline that delivers breast-cancer risk integrated with polygenic risk scores, monogenic variants, family history, and clinical factors, emphasizing operati...